Bottom Line:
Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R(2)~0.76-0.80 between individual cells and R(2)~0.69 between 50 pg total RNA replicates.Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R(2)~0.80).Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.

Affiliation: Research and Development, Illumina, Inc, San Diego, California, United States of America. jfan@illumina.com

ABSTRACT

Background: We have developed a high-throughput amplification method for generating robust gene expression profiles using single cell or low RNA inputs.

Methodology/principal findings: The method uses tagged priming and template-switching, resulting in the incorporation of universal PCR priming sites at both ends of the synthesized cDNA for global PCR amplification. Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R(2)~0.76-0.80 between individual cells and R(2)~0.69 between 50 pg total RNA replicates. Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R(2)~0.80). Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.

Conclusions/significance: In summary, our method facilitates whole-genome gene expression profiling in contexts where starting material is extremely limiting, particularly in areas such as the study of progenitor cells in early development and tumor stem cell biology.

pone-0030794-g003: Intensity and detected probe concordance comparisons between low and higher 1 ng inputs.Raw signal intensity correlations between (A) 50 pg (x-axis) and 1 ng (y-axis) UHR total RNA; (B) 10 pg (x-axis) and 1 ng (y-axis) UHR total RNA; (C) single HeLa cell (x-axis) and 1 ng (y-axis) HeLa total RNA. The overlapping sets of detected probes between the low and higher inputs are shown for both the RNA equivalent (D, E) and single cell (F) inputs. All probe values shown are at a threshold of p<0.01.

Mentions:
In order to determine the extent to which the gene expression profiles obtained at low input levels correlated with those obtained with higher inputs, we directly compared raw signal intensities between the lower and higher inputs. Correlations between 50 pg and 1 ng total RNA typically yielded R2∼0.80 (Fig. 3A, Table 1), whereas correlations between 10 pg and 1 ng total RNA typically yielded R2∼0.59 (Fig. 3B). Single cell correlations with 1 ng total RNA, derived from a corresponding bulk cell culture, yielded R2∼0.80 (Fig. 3C, Table 1). At p<0.01, we detected ∼13443 and 10180 probes for the 50 and 10 pg RNA inputs, respectively, whilst detecting ∼14156 and 11083 probes for the 5-cell and single cell inputs (Table 1), respectively. This level of sensitivity represents approximately 77% (50 pg), 58% (10 pg), 80% (5-cell) and 63% (single cell) of the total number of probes detected in the higher, standard inputs. Furthermore, when the lists of probes detected (p<0.01) in the lower inputs were intersected with those detected in the higher 1 ng inputs, we obtained probe concordance values of ∼96.6%, 97.1% and 97.4% for the 50 pg (Fig. 3D, Table 1), 10 pg (Fig. 3E) and single HeLa cells (Fig. 3F, Table 1), respectively. The percentage of false positive probes detected in the lower inputs was <2% of the total number of probes detected in the higher standard inputs. Taken together these results demonstrate that our assay is sufficiently sensitive to reliably detect, in low inputs, most of the genes that are detected at standard higher inputs, and that the expression profiles derived from these lower inputs accurately recapitulate those obtained in higher inputs.

pone-0030794-g003: Intensity and detected probe concordance comparisons between low and higher 1 ng inputs.Raw signal intensity correlations between (A) 50 pg (x-axis) and 1 ng (y-axis) UHR total RNA; (B) 10 pg (x-axis) and 1 ng (y-axis) UHR total RNA; (C) single HeLa cell (x-axis) and 1 ng (y-axis) HeLa total RNA. The overlapping sets of detected probes between the low and higher inputs are shown for both the RNA equivalent (D, E) and single cell (F) inputs. All probe values shown are at a threshold of p<0.01.

Mentions:
In order to determine the extent to which the gene expression profiles obtained at low input levels correlated with those obtained with higher inputs, we directly compared raw signal intensities between the lower and higher inputs. Correlations between 50 pg and 1 ng total RNA typically yielded R2∼0.80 (Fig. 3A, Table 1), whereas correlations between 10 pg and 1 ng total RNA typically yielded R2∼0.59 (Fig. 3B). Single cell correlations with 1 ng total RNA, derived from a corresponding bulk cell culture, yielded R2∼0.80 (Fig. 3C, Table 1). At p<0.01, we detected ∼13443 and 10180 probes for the 50 and 10 pg RNA inputs, respectively, whilst detecting ∼14156 and 11083 probes for the 5-cell and single cell inputs (Table 1), respectively. This level of sensitivity represents approximately 77% (50 pg), 58% (10 pg), 80% (5-cell) and 63% (single cell) of the total number of probes detected in the higher, standard inputs. Furthermore, when the lists of probes detected (p<0.01) in the lower inputs were intersected with those detected in the higher 1 ng inputs, we obtained probe concordance values of ∼96.6%, 97.1% and 97.4% for the 50 pg (Fig. 3D, Table 1), 10 pg (Fig. 3E) and single HeLa cells (Fig. 3F, Table 1), respectively. The percentage of false positive probes detected in the lower inputs was <2% of the total number of probes detected in the higher standard inputs. Taken together these results demonstrate that our assay is sufficiently sensitive to reliably detect, in low inputs, most of the genes that are detected at standard higher inputs, and that the expression profiles derived from these lower inputs accurately recapitulate those obtained in higher inputs.

Bottom Line:
Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R(2)~0.76-0.80 between individual cells and R(2)~0.69 between 50 pg total RNA replicates.Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R(2)~0.80).Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.

Affiliation:
Research and Development, Illumina, Inc, San Diego, California, United States of America. jfan@illumina.com

ABSTRACT

Background: We have developed a high-throughput amplification method for generating robust gene expression profiles using single cell or low RNA inputs.

Methodology/principal findings: The method uses tagged priming and template-switching, resulting in the incorporation of universal PCR priming sites at both ends of the synthesized cDNA for global PCR amplification. Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R(2)~0.76-0.80 between individual cells and R(2)~0.69 between 50 pg total RNA replicates. Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R(2)~0.80). Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.

Conclusions/significance: In summary, our method facilitates whole-genome gene expression profiling in contexts where starting material is extremely limiting, particularly in areas such as the study of progenitor cells in early development and tumor stem cell biology.